General Person Research Articles

Implementasi Kebijakan BLT Berdasarkan Analisis Van Meter Dan Van Horn (Magang Kerja Di Desa Sidomulyo Kecamatan Batu Kota Batu)

Direct Cash Assistance (BLT) is direct assistance in the form of a certain amount of cash for households that really need it, namely households that are included in the very poor category. This program was launched by the government as social protection for the poor to reduce the negative impact of The policy of adjusting compensation to reduce fuel subsidies is to help poor people meet their basic needs. The objectives of this research are (1) to find out the implementation of the Direct Cash Assistance program policy in the Sidomulyo Village area, Batu District, Batu City. (2) to find out what are the supporting and inhibiting factors from the government of the village government in implementing the Direct Cash Assistance policy in Sidomulyo area, Batu District, Batu City. The type of research used by researchers is descriptive research with a qualitative research approach, the focus of the research is (1) Implementation of public policy (2) Direct Cash Assistance Program in Sidomulyo Village (3) Analysis of Van Meter and Van Horn so that the informants in this research are (1 )Head of Sidomulyo Village, as general person in charge of the area. (2) Village Secretary as person in charge of administration (3) Head of the People's Welfare Section as person in charge of the Direct Cash Assistance Program in Sidomulyo Village.

Multifunctional organohydrogel via the synergy of dialdehyde starch and glycerol for motion monitoring and sign language recognition

Conductive hydrogel which belongs to a type of soft materials has recently become promising candidate for flexible electronics application. However, it remains difficult for conductive hydrogel-based strain sensors to achieve the organic unity of large stretchability, high conductivity, self-healing, anti-freezing, anti-drying and transparency. Herein, a multifunctional conductive organohydrogel with all of the above superiorities is prepared by crosslinking polyacrylamide (PAM) with dialdehyde starch (DAS) in glycerol-water binary solvent. Attributing to the synergy of abundant hydrogen bonding and Schiff base interactions caused by introducing glycerol and dialdehyde starch, respectively, the organohydrogel achieved balanced mechanical and electrical properties. Besides, the addition of glycerol promoted the water-locking effects, making the organohydrogel retain the superior mechanical properties and conductivity even at extreme conditions. The resultant organohydrogel strain sensor exhibits desirable sensing performance with high sensitivity (GF = 6.07) over a wide strain range (0–697 %), enabling the accurate monitoring of subtle body motions even at −30 °C. On the basis, a hand gesture monitor system based on the organohydrogel sensors arrays is constructed using machine learning method, achieving a considerable sign language recognition rate of 100 %, and thus providing convenience for communications between the hearing or speaking-impaired and general person.

Web Real Time Communication (RTC)

Web Real-Time Communication (WebRTC) is an open-source challenge that allows real-time communique talents immediately within internet browsers and cellular applications. It permits peer- to-peer communique, which includes audio, video, and information sharing, without the want for any extra plugins or 1/3-party software program. WebRTC abstracts the complexities of organising direct communique channels among devices, allowing developers to integrate seamless real-time conversation functionalities into web applications. It leverages a aggregate of standardized protocols, such as Session Initiation Protocol (SIP) and Interactive Connectivity Establishment (ICE), and JavaScript APIs to allow steady and efficient conversation among customers, enhancing the general person enjoy for diverse online collaboration, conferencing, and conversation programs.

Meaning and Usage of Jibun in Oral Japanese

This study analyzes the meaning of using the word Jibun in spoken language taken from the story of a smartphone game entitled "Twisted Wonderland". This study uses conversational data in the game as research data. This study aims to recognize the various meanings and uses of the word Jibun in the Japanese spoken language. This qualitative research uses a descriptive method, which describes the data obtained and concludes the results through categories formed through the results of data description and analysis. Electronic games are data sources, mainly from the Heisei and Reiwa eras up to the time of this research. The result found that the use of the word Jibun as Saikikei, the use of the word Jibun as a personal pronoun, and the word Jibun as a word that refers to a general person. However, compared to the previously studied theory, some differences in usage were found. The use of Jibun as Saikikei in spoken language has differences in the order of subject positions because, in this study, the data used is part of a conversation and uses spoken language, so the word order does not match the standard language.

Discrimination of clothing materials from smartphone camera images

AbstractInformation on fabric material is necessary in washing and ironing clothing. However, indication on a care tag may peel off or the tag may come off due to deterioration over time. Discrimination of the material from the fabric itself is not easy for a general person. Estimating the material of an object is one of the challenging tasks in computer vision. This paper deals with the identification of cloth materials using computer vision. We studied a method to discriminate the fabric material from the image of clothing taken by a smartphone camera. First, we investigated the relationship between image resolution and discrimination accuracy using a convolutional neural network (CNN). As a result, we observed that the accuracy changes with resolution and that the resolution at which the accuracy is highest differs depending on the material. Based on these results, we proposed a fabric material discrimination method using multi‐resolution images by combining two CNNs. As a result of the evaluation experiment, the proposed method discriminated six kinds of fabric materials with 87.1% accuracy, and the accuracy was significantly higher than that of the comparison method without using multi‐resolution images.

The efficacy and safety of catheter balloon dilatation in the treatment of dysphagia after stroke: A protocol for systematic review and meta-analysis.

Dysphagia is a serious complication after stroke, which has a significant influence on the health as well as life quality of global people. Patients with dysphagia tend to be a higher risk rate of an aspiration than general person. Catheter balloon dilatation is an additional therapy for treating dysphagia in recent years, which can improve the symptom of achalasia of cricopharyngeal muscle. This research will be used for confirming the efficacy and safety of the catheter balloon dilatation for resolving dysphagia. We intend to search literature related to the research in different databases, for instance, China National Knowledge Infrastructure, Wanfang Data, PubMed, Cochrane Library, and Embase up to January 2022. Literature selection, data collection, as well as assessment of bias risk, will be carried out by 2 independent researchers. Data analysis will be conducted by using Stata and review manager 5.4. The results will be submitted to a peer-reviewed journal. The research will verify whether or not catheter balloon dilatation can improve dysphagia by submitting high-quality data syntheses. CRD42022358433.

The Leadership of The Head Nurse and The Motivation of Nurses in The Pediatric Service of The National Hospital Guido Valadares Dilli Timor-Leste

Introduction: The leadership of the head nurse and the motivation of the nurses of the service is a fundamental indicator to evaluate the quality of health care in pediatrics of the HNGV Dili. The leader is to manage the strongest strengths of the organization and employees, so that they work more or more effectively, in the daily service. Objective: To analyze the impact of the leadership of the head nurse on the motivation of nurses of the pediatric service of HNGV Díli Timor-Leste. Methodology: The study is descriptive of the cross-sectional and analytical type, of quantitative approach; The sample consisted of 45 nurses (10 head nurses and 35 nurses) from the pediatrics service of HNGV Timor-Leste, in functions at the time of questionnaire application (nurses: 40%; nurses: 60%). In the total sample of 70 respondents in this study, 25 were excluded and did not return. Results: The majority of workers (27.77 %) consider the employer a disciplined person who guides and directs their subordinates in the ward. In general, a humble and responsible person who makes decisions listening to the opinion of his collaborators was made. Only 8 respondents in 35 (23%) consider that the head nurse is not directly involved in social activities and does not seek possibilities to help people. Most consider the boss an efficient and effective person. Only 6 of the 35 respondents (17%) reported that the head nurse gives little support in formal and non-formal education to subordinates. The majority of nurses surveyed (8 out of 10:80%) recognize that they work in a way that motivates their subordinates to provide good quality nursing care. Only one of the head nurses (10%) does not consider the presence and delays of its members daily and the fulfillment of important schedules. Conclusion: The results express that the collaborators recognize that the work developed by the head nurses has an impact on their motivation and the work they develop, especially on the quality of nursing care provided. It is therefore important in the future that there is greater concern among hospital bosses and managers about the strategies to be defined to strengthen work teams and improve the care provided especially with the definition of quality indicators, the strengthening of in-service training and teamwork. From the results we recognize that leadership has influenced the motivation of the team and the quality of care provided.

PERSONALITY PREDICTION MODEL USING DEEP LEARNING

The project depends on distinguishing the character of a singular utilizing AI calculations and large 5 models. The character of a human assumes a significant part in his own and proficient life. These days, numerous associations have likewise begun shortlisting the competitors in view of their character as this builds the proficiency of the work in light of the fact that the individual is working in what he is great at as opposed to what he is compelled to do. The Big Five model is otherwise called the Five-Factor Model (FFM) and OCEAN model was created in the mid 1980s as per numerous mental hypotheses. Whenever measurable examination is applied to character study information, a few words used to depict the individual and these words give a rundown of the general person or character of the individual precisely. Character as seen as a brand name of mindfulness, conduct and energetic models from natural and ecological parts. It shows individuals as they quarrel about contemplations, ways of behaving and sentiments. Character attributes don't change in that frame of mind as they give the sensation of being out of control the conspicuous characteristics of an individual with a predictable quality as opposed to mirroring a specific character. Character contrasts ought not out of the ordinary to forestall the justification behind the bar or struggle in the subject of work or schooling. Along these lines, in enrolling an everyday schedule of work, one must be isolated.

“Cutting Up a Chicken with a Cow-Cleaver”—Confucianism as a Religion in Japan’s Courts of Law

This paper explores the Naha Confucius Temple case, resolved by the Supreme Court in February 2021, in light of postwar decisions on Articles 20 and 89 of the Japanese constitution. Religion is a contested category in Japanese legislation, appearing both in the constitution and in laws regulating the freedoms and restrictions of legally registered religious organizations. While the organization behind the Confucius Temple in Naha was registered as a general corporate juridical person, the majority opinion sided with the plaintiffs’ argument that the free lease granted to the temple by the municipality of Naha constituted a violence of the ban on public sponsorship of religious institutions and activities. In order to reach their decision, the Supreme Court and the lower courts not only had to decide on whether Confucianism was a religion or not, but also on whether the organization behind the temple—a group dedicated to the history and memory of the Chinese immigrant community in Naha—should in fact be considered a religious organization. The outcome of the case is a good example of religion-making in courts of law, with a central institution of power employing notions of sui generis religion to regulate and define civil actors.

A Novel SRTSR Model for Cross-Resolution Person Re-Identification

Compared to the general person re-identification (re-id), pedestrian images in cross-resolution person re-id tasks always have variant resolutions, thus the resolution mismatching problem between low-resolution (LR) images and high-resolution (HR) images significantly limits the performance of neural networks. The general solution is to introduce interpolation methods or super-resolution (SR) module to normalize all the images to the same resolution. Unfortunately, current SR methods can only upscale the entire image to a certain scale, but fail to unify the resolution of images with different width-to-height ratio. To solve this problem, we propose a Specific-Resolution-Targeted Super-Resolution (SRTSR) embedded person re-id method. Instead of using deep CNN-based SR methods, our SRTSR network consists of a fast and light-weight feature learning module with a self-adaptive Swish (SA-Swish) as its activation function to improve its performance, and a specific-resolution-targeted upscale module to upscale the images to any specific resolution. Compared to the traditional upscale module which can only accept the upscale factor for the entire image, our upscale module can either accept two independent and arbitrary upscale factors for either height and width, e.g., $2.4\times $ for height and $3.1\times $ for width, or any specific resolution, e.g., $256\times 128$ , helping to unify the resolution of images with different width-to-height ratio. Extensive experiments are conducted and the result shows that the performance of our method is over the SR-based state-of-the-art person re-id methods on common re-id benchmarks.

Semantic-Aware Occlusion-Robust Network for Occluded Person Re-Identification

In recent years, deep learning-based person re-identification (Re-ID) methods have made significant progress. However, the performance of these methods substantially decreases when dealing with occlusion, which is ubiquitous in realistic scenarios. In this article, we propose a novel semantic-aware occlusion-robust network (SORN) that effectively exploits the intrinsic relationship between the tasks of person Re-ID and semantic segmentation for occluded person Re-ID. Specifically, the SORN is composed of three branches, including a local branch, a global branch, and a semantic branch. In particular, the local branch extracts part-based local features, and the global branch leverages a novel spatial-patch contrastive loss (SPC) to extract occlusion-robust global features. Meanwhile, the semantic branch generates a foreground-background mask for a pedestrian image, which indicates the non-occluded areas of the human body. The three branches are jointly trained in a unified multi-task learning network. Finally, pedestrian matching is performed based on the local features extracted from the non-occluded areas and the global features extracted from the whole pedestrian image. Extensive experimental results on a large-scale occluded person Re-ID dataset (i.e., Occluded-DukeMTMC) and two partial person Re-ID datasets (i.e., Partial-REID and Partial-iLIDS) show the superiority of the proposed method compared with several state-of-the-art methods for occluded and partial person Re-ID. We also demonstrate the effectiveness of the proposed method on two general person Re-ID datasets (i.e., Market-1501 and DukeMTMC-reID).

Relationship between physical activity and depression according to the presence of disease in koreans over the Age of 40

Purpose The purpose of this study was to investigate the relationship between physical activity and depression according to the presence of disease. Methods A survey and basic assessment were conducted for 2,754 (Male=1,025 and Female=1,729) aged 40 and over who participated in the rural-based cohort study. The survey included physical activity, depression scale and disease preservation. The basic assessment measured height, weight, and body fat percentage. The measured data were analyzed by using logistic regression to examine the relationship between physical activity and depression prevalence. Results First, physical activity reduced the prevalence of depression by 33% and 51%, respectively, in the general population and in patients with the disease. Second, physical activity once or twice per week reduced the prevalence of depression in patients with disease by 51%, and at least three physical activities reduced the prevalence of depression by 37% in the general population and 33% of patients with disease. Third, physical activity less than 150 minutes per week reduced the prevalence of depression in patients with disease by 43%, and physical activity of more than 150 minutes and less than 300 minutes per week reduced the prevalence of 43% of the general population and 52% of patients with disease. Physical activity over 300 minutes per week had a 38% reduction in the prevalence of depression in the general population. Conclusions This study suggests that the level of physical activity suggested by the ACSM guidelines is appropriate to reduce the prevalence of depression. In addition, the patients with the disease was found to be effective with less frequency and amount of physical activity than the general person.

Intuitive Gait Pattern Generation for an Exoskeleton Robot

Exoskeleton robots are being studied and developed in various forms according to user. Among them, the most concentrated area is the lower limb exoskeleton robot for “walking,” which is the basic exercise of paralyzed patients. In this study, we utilize the gait cycle, speed, and stride, which are important dependent factors of gait, and not the control technique that uses the predefined gait pattern using the average value of the gait data of the general person used by the existing rehabilitation exoskeleton robot. By creating an end-point reference using a walking element and inverse kinematics, and by using a dynamic movement primitive technique to learn the gait data of the general public, generating the gait patterns of various walking environments without storing them in advance is possible. In this paper, we applied this method to the exoskeleton robot and show robot to generate various strides gait pattern by experiments.

Asymmetric person re-identification: cross-view person tracking in a large camera network

Person re-identification (RE-ID) is critical and crucial for tracking people across multiple camera views, and hence, the piece-wise tracklets of each person from different locations can be connected. In this paper, we first review the development of person RE-ID and present its challenges. Subsequently, we introduce our recent development on asymmetric distance metric learning and the asymmetric person RE-ID modeling of the largely unsolved open-topic problems. Existing metric learning methods for person RE-ID usually ignore the characteristics of feature transformations between different camera views. The advantage of asymmetric metric is that it can model inconsistent feature transformations between different camera views. Except for being applied to general person RE-ID problem, asymmetric model can also be applied to cross-modality RE-ID, low-resolution RE-ID, attribute-image RE-ID, unsupervised RE-ID and partial RE-ID. Finally, we discuss the future development of person RE-ID.

Distance Metric Learning via Iterated Support Vector Machines.

Distance metric learning aims to learn from the given training data a valid distance metric, with which the similarity between data samples can be more effectively evaluated for classification. Metric learning is often formulated as a convex or nonconvex optimization problem, while most existing methods are based on customized optimizers and become inefficient for large scale problems. In this paper, we formulate metric learning as a kernel classification problem with the positive semi-definite constraint, and solve it by iterated training of support vector machines (SVMs). The new formulation is easy to implement and efficient in training with the off-the-shelf SVM solvers. Two novel metric learning models, namely positive-semidefinite constrained metric learning (PCML) and nonnegative-coefficient constrained metric learning (NCML), are developed. Both PCML and NCML can guarantee the global optimality of their solutions. Experiments are conducted on general classification, face verification, and person re-identification to evaluate our methods. Compared with the state-of-the-art approaches, our methods can achieve comparable classification accuracy and are efficient in training.

Development of fast measurements of concentration of NORM U-238 by HPGe

Naturally Occureed Radioactive Material (NORM) generated from the origin of earth can be found all around us and even people who are not engaged in the work related to radiation have been exposed to unnecessary radiation. This NORM has a potential risk provided that is concentrated or transformed by artificial activities. Likewise, a development of fast measruement method of NORM is emerging to prevent the radiation exposure of the general public and person engaged in the work related to the type of business related thereto who uses the material in which NORM is concentrated or transfromed. Based on such a background, many of countries have tried to manage NORM and carried out regulatory legislation. To effienctly manage NORM, there is need for developing new measurement to quickly and accurately analyze the nuclide and concentration. In this study, development of the fast and reliable measurement was carried out. In addition to confirming the reliability of the fast measurement, we have obtained results that can suggest the possibility of developing another fast measurement. Therefore, as a follow-up, it is possible to develop another fast analytical measurement afterwards. The results of this study will be very useful for the regulatory system to manage NORM. In this study, a review of two indirect measurement methods of NORM U-238 that has used HPGe on the basis of the equilibrium theory of relationships of mother and daughter nuclide at decay-chain of NORM U-238 has been carried out. For comparative study(in order to know reliabily), direct measurement that makes use of alpha spectrometer with complicated pre-processing process was implemented.

Gray Color Image and Preference for Fashion Material

As standards of living rise, sensibility has had powerful impacts on consumers decisions. Especially, it is seen that the value of products increases due to color images arousing emotions, which reflect several senses. Particularly, gray is an important standardized color not only for fashion but also numbers of the design field. Therefore, it is expected to feel several images with emotional arousal from gray colors visualized through fashion materials and we will evaluate the purchase preference as well and expect it to be useful in the actual fashion industry scene. To select adjectives of images with emotional arousal for evaluating the experiment of the images, we selected and extracted final images of sensibility from surveys on domestic fashion sites online. Experimental group for evaluation experiment was divided into color expert group and general person group. Seven materials were selected based on the standards that represent four seasons. The stage of gray color is divided into high, mid, and low brightness based on Munsell Gray Scale System. The evaluation scale used the Semantic Discriminant scale method (SD) and the emotional image was prepared in five stages to evaluate the material. Results from the experiment of evaluating the images showed that the color expert group and the general group felt various emotions, but the color expert group felt a more diverse emotional image. Especially, the materials with high brightness of feeling showed the most various emotional images regardless of group. There was a difference in purchase preference between the two groups to the brightness level by fashion material. Hence, the research suggests a useful guide for designing fashion products by presenting several sensibilities and preferences regarding gray color which is one of the representative standard colors in fashion fields.

The Effect of Posting Source Type Information on Brand Reliability, Product Attitude and Purchase Intention - Comparison of general person posting and corporate posting in Sina Weibo -

The Effect of Posting Source Type Information on Brand Reliability, Product Attitude and Purchase Intention - Comparison of general person posting and corporate posting in Sina Weibo -

Putting the pieces together: Revealing face–voice integration through the facial overshadowing effect

ABSTRACTTwo experiments are reported which explore the limits of the facial overshadowing effect on voice recognition. In Experiment 1, the facial overshadowing effect was replicated. Voice recognition was significantly impaired when the voice had been studied in the presence of the face rather than when studied alone. However, this effect was removed when the accompanying face was inverted. In Experiment 2, the facial overshadowing effect was replicated using more realistic moving faces rather than static faces through presentation of a video sequence at study. Surprisingly, the magnitude of the facial overshadowing effect was not influenced by whether faces were static or dynamic. Moreover, the effect remained even under temporal asynchrony. Together, these results show the facial overshadowing effect to be a robust phenomenon. However, it appears to depend critically on one factor: the facial nature of the distraction. The results are discussed in terms of the integration of faces and voices in a recognition context, and in terms of a holistic view of face–voice processing in a more general person perception framework. This offers an explanation of current findings, and serves to guide predictions for future work.

Human Detection by Fourier Descriptors and Fuzzy Color Histograms with Fuzzyc-Means Method

[abstFig src='/00280004/07.jpg' width='300' text='Result of specific person detection in Tsukuba Challenge' ] It is difficult to use histograms of oriented gradients (HOG) or other gradient-based features to detect persons in outdoor environments given that the background or scale undergoes considerable changes. This study involved the segmentation of depth images. Additionally, P-type Fourier descriptors were extracted as shape features from two-dimensional coordinates of a contour in the segmentation domains. With respect to the P-type Fourier descriptors, a person detector was created with the fuzzyc-means method (for general person detection). Furthermore, a fuzzy color histogram was extracted in terms of color features from the RGB values of the domain surface. With respect to the fuzzy color histogram, a detector of a person wearing specific clothes was created with the fuzzyc-means method (specific person detection). The study includes the following characteristics: 1) The general person detection requires less number of images used for learning and is robust against a change in the scale when compared to that in cases in which HOG or other methods are used. 2) The specific person detection gives results close to those obtained by human color vision when compared to the color indices such as RGB or CIEDE. This method was applied for a person search application at the Tsukuba Challenge, and the obtained results confirmed the effectiveness of the proposed method.