Reviewerly/exHarmony huggingface dataset:
Computational trademark infringement and adjudication

The likelihood of confusion standard is the linchpin of trade mark infringement. This chapter explores AI's liberating effect on bounded rationality and consumers' need to rely on trade marks as decisional heuristics. This shift raises new questions about liability for trade mark infringement when digital platforms such as Amazon recommend counterfeit products. The chapter also explores AI-assisted adjudication of trade mark disputes from conception to implementation. It draws on theoretical models and working prototypes in adjacent areas of the law to reveal the opportunities and challenges that trade mark scholars and practitioners should consider. Bias, accountability and data availability are well-known concerns with AI deployment. While these are legitimate issues, each can be significantly mitigated or, in some cases, comprehensively addressed.
USER PERSONAS TO GUIDE TECHNOLOGY INTERVENTION DESIGN TO SUPPORT CAREGIVER-ASSISTED MEDICATION MANAGEMENT

Abstract Informal caregivers often help manage medications for people with ADRD. Caregiver-assisted medication management has the potential to optimize outcomes for caregivers and people with ADRD, but is often associated with suboptimal outcomes. We used the user-centered design persona method to represent the needs of ADRD caregivers who manage medications for people with ADRD to guide future design decisions for technology interventions. Data were collected through virtual contextual inquiry in which caregivers (Nf24) sent daily multimedia text messages depicting medication management activities for seven days each, followed by an interview that used the messages as prompts to understand medication management needs. We applied the persona development method to the data to identify distinct caregiver personas, i.e., evidence-derived groups of prospective users of a future intervention. We used team-based affinity diagramming to organize information about participants based on intragroup (dis)similarities, to create meaningful clusters representing intervention-relevant attributes. We then used group consensus discussion to create personas based on attribute clusters. The six identified attributes differentiating personas were: 1. medication acquisition, 2. medication organization, 3. medication administration, 4. monitoring symptoms, 5. care network, 6. technology preferences. Three personas were identified based on differences on those attributes: Regimented Ruth (independent, proactive, tech savvy, controls all medications), Intuitive Ian (collaborative, uses own judgment, some technology, provides some medication autonomy), Passive Pamela (reactive, easy going, technology novice, provides full medication autonomy). These personas can be used to guide technology intervention design by evaluating how well intervention designs support each of them.
Lifebuoy Soap Stock Decision Making System Of Neighbourhood 5 And 6 Pagar Dewa Urban Village Bengkulu

A product provider must make the right decisions in predicting the amount of new stock that will be distributed to stalls. Sales of lifebuoy soap in Neighbourhood OF 5 and 6 experienced a difference in the number of sales each month. This of course will make it difficult for the supplier of goods to know the exact number of products that must be stocked. To be able to overcome this and increase the realization of sales from each stall, it is necessary to have a fast and appropriate prediction process that can overcome problems in determining the amount of distribution of new stock. The method used is the Fuzzy Tsukamoto method and is written in the PHP programming language. Where this method is chosen because it is a method of counting with variable words, instead of counting with numbers, human expert systems can be implemented into machine language easily and efficiently. Identification of user needs is needed in the design to determine what features can be used in the system and use story boards to get an overview of the system. System testing using black box by testing all buttons on the application. Based on the results of the study, it can be concluded that this system helps simplify and shorten the time in determining the amount of fulfillment of new stock requests
Design of Customer Satisfaction E-Questionnaire and Chatbot System at PT. PLN (Persero) Bengkulu City Website Based

Customer satisfaction is a form of feeling happy or disappointed someone who comes from a comparison between his impression of the performance of a service or goods against his expectations. PT PLN (Persero) Bengkulu City in the implementation of the implementation of the provision of electricity services certainly does not escape the existence of problems. The problems that arise are regarding customer complaints about the services provided by the problematic company. Seeing from these problems the solutions that can be given to overcome their complaints, it is very suitable to make an e-questionnaire system and chat customer complaints process using a website-based chatbot. This system will apply the Likert scale calculation method as a method to measure the level of customer satisfaction which will make it easier to get the results of filling out the questionnaire. In addition, this system will later create a complaint chat using a chatbot, which is a robotic chat service with artificial intelligence or AI (Artificial Intelligent) that imitates human conversations through messages that will answer customer questions regarding service problems provided by the company. This will certainly make it much easier for the company to get results from filling out questionnaires and make it easier for customers to make complaints regarding problems with the services provided. The results of this study have created an E-Questionnaire system for Customer Satisfaction and a website-based Complaint Chatbot.
A Preliminary Study of the Influence of Social Media Engagement on Information Seeking Behavior among the Secondary School Students

The aim of conducting this research is to examine the influence of social media engagement on information-seeking behavior. There is lack of concern about generalizability and implementation towards emphasizing the effects of social media engagement on information-seeking behavior in Malaysia. A close-ended questionnaire was distributed to the students to conduct the data collection for this research. The data was collected from students and was analyzed using SPSS version 26. Findings show that two hypotheses were accepted; Novelty and Perceived Usability have a positive and significant relationship between information-seeking behavior, while Focus Attention and aesthetics were found insignificant for information-seeking behavior. Keywords: Social media, information-seeking behavior, Social media engagement, aesthetic, education eISSN: 2398-4287 © 2022. The Authors. Published for AMER ABRA cE-Bs by E-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under the responsibility of AMER (Association of Malaysian Environment-Behavior Researchers), ABRA (Association of Behavioral Researchers on Asians), and cE-Bs (Centre for Environment-Behavior Studies), Faculty of Architecture, Planning &amp; Surveying, Universiti Teknologi MARA, Malaysia.
A study of update request comments in Stack Overflow answer posts

Comments play an important role in updating Stack Overflow (SO) posts. They are used to point out a problem (e.g., obsolete answer and buggy code) in a SO answer or ask for more details about a proposed answer. We refer to this type of comment as update request comments (URCs), which may trigger an update to the answer post and thus improve its quality. In this study, we manually analyze a set of 384 sampled SO answer posts and their associated 1,221 comments to investigate the prevalence of URCs and how URCs are addressed. We find that around half of the analyzed comments are URCs. While 55.3% of URCs are addressed within 24 h, 36.5% of URCs remain unaddressed after a year. Moreover, we find that the current community-vote mechanism could not differentiate URCs from non-URCs. Thus many URCs might not be aware by users who can address the issue or improve the answer quality. As a first step to enhance the awareness of URCs and support future research on URCs, we investigate the feasibility of URC detection by proposing a set of features extracted from different aspects of SO comments and using them to build supervised classifiers that can automatically identify URCs. Our experiments on 377 and 289 comments posted on answers to JavaScript and Python questions show that the proposed URC classifier can achieve an accuracy of 90% and an AUC of 0.96, on average.
Piipperin rajoitukset ja mahdollisuudet PC-pelien musiikissa

Abstract&#x0D; The article presents a method using which it is possible to accurately transcribe PC speaker music in games. The idea of the transcription method is to modify the DOSBox emulator so that it records PC speaker events (note onset times and frequencies) while playing the game. This results in an initial transcription which can be processed using music notation software.&#x0D; Using the transcription method, music from two PC games are transcribed and analyzed. In Alley Cat (1984), an impression of polyphony is achieved by playing sounds in different registers close to each other. In Stunts (1990), a large number of PC speaker events are created to produce polyphony, vibrato and glissandos. The analyses show examples of restrictions and possibilities when composing PC speaker music. The article presents a method using which it is possible to accurately transcribe PC speaker music in games. The idea of the transcription method is to modify the DOSBox emulator so that it records PC speaker events (note onset times and frequencies) while playing the game. This results in an initial transcription which can be processed using music notation software.
VM queuing optimal scheduling in cloud using heuristic ant colony optimal based multi-objective genetic approach

The usages of cloud based applications are increasing tremendously. The cloud computing task distribution is an unknown polynomial time issue that is challengeable to find the optimal solution. In solve above mentioned issue with large amount user’s job requests, heuristic ant colony optimal based multi-objective genetic (HACOMOG) approach based job allocation and resource optimization is proposed. Utilization basis scheduler recognizes the task order and optimal resources to be scheduled. The primary contribution of the proposed technique is to develop several online techniques to find solution for the virtual machines (VM) Packing problem sharing-aware and for performing a comprehensive number of studies in order to assess their efficiency with online sharing algorithms. The proposed algorithm considers the utilization basis scheduler output and identified the optimzed task allocation technique based on job execution time, MakeSpan and throughput. The experimental outcomes show that the proposed HACOMOG Algorithm reduces 0.70 seconds job execution time (JET), 0.13 MakeSpan and improve 1.98 throughput on given parameters for 100, 200, and 500 tasks with conventional methodologies.
Smart Home Tech: an interface to provide feedback to caregivers of persons living with cognitive impairment

Abstract Background Home‐based sensor technologies can detect information on daily activities, such as sleep, activity level, and time spent together. This is relevant information for care partners of individuals with cognitive impairment as it can detect early changes in daily activities and cognition. The challenge is how to present thousands of data points to care partners in real‐time, allowing them to make adjustments in their daily routine to help reduce burden. Method The Collaborative Aging Research using Technology (CART) sensor platform was installed in 4 Ottawa homes of persons with cognitive impairment and their care partner. This system includes contact and motion sensors to assess home activity, a smart watch to record steps and sleep patterns, a bed sensor, and medication tracking pillboxes. Questions regarding areas of stress, the types of information that caregivers would like to receive, and how to receive their data were posed in focus group discussions involving caregivers with and without the sensor platform. An interface was designed based on participant input. Result Eight care partners (75% female) aged 30 to 81 participated in focus groups that obtained their opinions on the usefulness of a feedback system, its content, layout, and frequency in which care partners would like to receive their sensor information. The majority of participants wished to be sent their sensor information on a weekly basis in easy to interpret graphical formats that summarized information for them. An algorithm that collects sensor data, parses appropriate measures; steps, sleep, time together in a room, and displays it in graphical representation, was developed. The user interface displays the daily summary compared to the weekly average, with the ability to navigate between day and weekly views. Conclusion Sensor‐based data needs to be displayed in an efficient and convenient manner if it is going to be used by care partners to help guide changes in behavior to reduce stress. This project designed an interface, based on user feedback. This system also has the potential to be used by clinicians to evaluate longitudinal cognitive decline. Next, we will provide participants with the CART system with sample visual reports and gather their feedback.
Variational Factorization Machines for Preference Elicitation in Large-Scale Recommender Systems

Factorization machines (FMs) are a powerful tool for regression and classification i n t he c ontext o f s parse observations, that has been successfully applied to collaborative filtering, e specially w hen s ide i nformation o ver u sers o r items is available. Bayesian formulations of FMs have been proposed to provide confidence i ntervals o ver t he p redictions m ade by the model, however they usually involve Markov-chain Monte Carlo methods that require many samples to provide accurate predictions, resulting in slow training in the context of large-scale data. In this paper, we propose a variational formulation of factorization machines that allows us to derive a simple objective that can be easily optimized using standard mini-batch stochastic gradient descent, making it amenable to large-scale data. Our algorithm learns an approximate posterior distribution over the user and item parameters, which leads to confidence intervals over the predictions. We show, using several datasets, that it has comparable or better performance than existing methods in terms of prediction accuracy, and provide some applications in active learning strategies, e.g., preference elicitation techniques.
Parallelizable synthesis of arbitrary single-qubit gates with linear optics and time-frequency encoding

We propose methods for the exact synthesis of single-qubit unitaries with high success probability and gate fidelity, considering both time-bin and frequency-bin encodings. The proposed schemes are experimentally implementable with a spectral linear-optical quantum computation (S-LOQC) platform, composed of electro-optic phase modulators and phase-only programmable filters (pulse shapers). We assess the performances in terms of fidelity and probability of the two simplest three-component configurations for arbitrary gate generation in both encodings and give an exact analytical solution for the synthesis of an arbitrary single-qubit unitary in the time-bin encoding, using a single-tone rf driving of the electro-optic modulators. We further investigate the parallelization of arbitrary single-qubit gates over multiple qubits with a compact experimental setup, both for spectral and temporal encodings. We systematically evaluate and discuss the impact of the rf bandwidth, which conditions the number of tones driving the modulators, and of the choice of encoding for different targeted gates. We moreover quantify the number of high-fidelity Hadamard gates that can be synthesized in parallel, with minimal and increasing resources in terms of driving rf tones in a realistic system. Our analysis positions spectral S-LOQC as a promising platform to conduct massively parallel single-qubit operations, with potential applications to quantum metrology and quantum tomography.
THE EFFECTIVENESS OF CLUSTERING TECHNIQUE IN IMPROVING STUDENTS’ WRITING SKILL IN NARRATIVE TEXT AT SMA NEGERI 21 MAKASSAR

This research aims to find out The Effectiveness of Clustering Technique in Improving Students’ Writing Skill In Narrative Text. This research was conducted at SMA Negeri 21 Makassar. The design of this research is Pre-Experimental Design. The population of this study was the first-grade students in academic years 2020/2021 in SMAN 21 Makassar, which was selected by using cluster random sampling technique, while the sample of this study was 30 students. The instrument of this study was a test that used pre-test and post-test.The mean score of the pre-test in content 71,1 was lower than post-test 80,6. From the t-test, the study found that the value of t-test in generic structure pre-test 20,62 was fair than t-table 1.538, and the value of t-test in generic structure post-test 38,71 was greater than t-table 1.538. There was a difference between the students’ writing before and after applying the clustering technique in the class. It shows that the Null Hypothesis (H0) was rejected and the alternative hypothesis (H1) was accepted. The result of the data shows that writing in terms of the generic structure of narrative text through the clustering technique was a fairly effective method to improving students' writing skills in narrative text.
Design and Control of an Active Stage for Suppressing Motion Induced Vibration in Optical Inspection Systems

Fast positioning and vibration suppression play important roles in virtually all tasks requiring high speed maneuvers with sufficient motion accuracy. One typical example is on the operation of optical inspection systems, which requires to perform product defect inspections by fast moving to the desired inspection locations and take images. Due to the inherent structural compliance and the inertial force generated during movement, residual vibrations would be inevitable and this implies that additional settling time would be required for avoiding blurred images. How to improve inspection quality and yield is therefore a traditional but non-trivial concern. In this work, a test stage built with elastomeric bearings and compliant structure mounted with a camera, is designed for developing control schemes. Through dynamic testing, the plant characteristics are identified and the mathematical model of the active stage is obtained. Both loop transmission shaping and input shaping methods are used as the first step to evaluate the effectiveness on suppression of motion-induced vibration. The positioning control results indicate that a 0.5% overshoot and a 0.09 second setting time or a 22 Hz bandwidth could be achieved. Finally, the stage is mounted on a linear servomotor to simulate the behavior during fast maneuver of typical AOI systems due to structure compliance. A webcam mounted on the stage is responsible to examine the effectiveness of vibration control in both of the acquired imaging quality and inspection yield. It is found that the time delay required for taking inspection clear image after arriving the destination is reduced from 9s to 0.5s. Thus the inspection yield could be significantly improved. In summary, this work successfully confirmed that the active stage control system can effectively reduce residual vibration during optical inspection. In the future, the developed stage and control scheme should be able to be applied in real design for improving the associate inspection efficiency.
A Novel Curved Surface Text Detection Method Based on Multi-channel Pseudo-color Images

Text detection has been widely used in automatic navigation, product recognition and language translation. In order to solve the problem of poor text detection on cylindrical-shape object by using the 2D image information, a novel method for text detection on the curved surface of bottled objects based on 3D point cloud is proposed in this paper. To improve the representation ability of texts on the surface of cylindrical objects, text image sequence of bottled objects are captured from multiple viewpoints, and the 3D point cloud of bottled object is reconstructed with multi-view image sequences. For enhancing the discrimination between multi-text instances, such features as the 3D coordinate, RGB and Stroke Width Transform (SWT) of the text are extracted to generate the multi-modal feature of the surface text. In order to make full use of the advanced target segmentation technology of the image, the graph rendering technology is first used to map the surface point cloud into a 2D grid, and then the grid cells are filled with multi-modal features to generate multi-channel pseudo-image, followed by using the U-Net network segments the pseudo image into individual text instances. For verifying the effectiveness of this proposed method, extensive experiments are carried out on the 3D text point cloud established by us. The accuracy, recall and F -score average of our method are 85.9%, 77.5% and 81.5% respectively. Compared with the classical algorithms such as PSENet and CRAFT, the accuracy is increased by 10.5% and 5.8% respectively, and the average of F -score is increased by 1.1 % and 0.6% respectively. The experimental results show that the proposed method can accurately detect the surface text on cylindrical objects such as bottles and cans.
ANALISIS KEAMANAN WEB NEW KUTA GOLF MENGGUNAKAN METODE VULNERABILITY ASSESSMENTS DAN PERHITUNGAN SECURITY METRIKS

Various crimes that are security threats that can occur when we are socially networked, one of them is virtual theft. New Kuta Golf has tournament standard field and the first course with a layout model link. Large mobility companies also make data processing even bigger and more web sites that are concerned with transactions and promotional media. This is a reference to obtain information about the security of the New Kuta Golf website. The data that has been obtained are carried out for the project work step, are: (1) To conduct a Vulnerability assessment. (2) Analyze the results of the scan. (3) Calculate security metrics from the results obtained from the scanning process. (4) Documentation of the installation process, and calculating security metrics. The results of the research then analyzed and discussed with a review of the theory that was embraced. From the results of the tests, the following results are obtained: (1) In carrying out website security testing can be done by Vulnerability Assessment uses the acunetix application to find detailed results. (2) Determining the security of a website can be determined using security metrics. (3) The results of the vulnerability assessment on http://newkutagolf.co.id has a high value.