Sales Promotion Tools Behavioral Responses -Myassignmenthelp.Com

Question: Discuss About The Sales Promotion Tools Behavioral Responses? Answer: Introduction Marketing management is the process of developing strategies and planning for the product or services, promotion, advertisement, and sales to reach desired customer segment. Every business in the competitive world needs the manager who maintains and monitor the process related to the marketing the products (Hollensen, 2015). Digital communication is one of the effective ways through which the managers can perform their activity of promoting a product easily (Lapidoth, 2017). The report includes the current value analysis and the marketing promotion plan. The beachfront motel that is selected for the analysis is Beachfront Voyager Motor Inn. Background The aim of the motel is to provide the luxuries suites and rooms to the customers with the lovely views of the suits. The aim of the company is to fulfill the needs and expectations of the customers which lead to the satisfaction of customers. Company overview Beachfront Voyager Motor Inn is on Tasmanias North West coast which is situated at Burnie. Burnie is a place that is located in the center of North West Coast; it is sited on the Bass Highway. Bass highway is a coastal drive that is dotted with the beautiful capes, villages, and headlands that is related by the lots of the white sandy beaches (Beachfront Voyager Motor Inn, 2017). This motel is placed in the front of the town's beach which helps the company is attracting the maximum number of customers who like to stay in the place where they can enjoy the view of the sea. The rooms of the hotels are categorized into three Categories Sea View Executive Suite and Balcony, Executive Suite and standard suite (Beachfront Voyager Motor Inn, 2017). The major facilities that are offered by the company include bar, car park, conference/function facilities, laundry, and restaurants. Target market of company Target markets refer to as the group of customers or potential customers to whom the company offers its product and services. In simple words, it can be said that it is a group who is most likely to buy the products and services offered by the customers (Bowie, Buttle, Brookes, Mariussen, 2016). Beachfront Voyager Motor Inn targets the customers who want motel at the beachside. The company offers the three different categories of rooms to the customers that include- Sea View Executive Suite and Balcony, Executive Suite and Standard Suite (Beachfront Voyager Motor Inn, 2017). Thus, the motel targets the customers arrived for the business meetings or for the visit purpose. The primary target of the company is the customers who like prefer Sea View Executive Suite and Balcony and these customers include the couples and family. Value of position compared to competitors The competitors of the Beachfront Voyager Motor Inn include Beachway Motel Restaurant, Waterfront Lodge Motel, and Mantra Lorne. These are the few motels that give strong competition to the company. Beachway Motel Restaurant is one of the strong competitors as it is having the rating of the 4.5 out of 5 which is quite high then the company. The company has the rating of 3.5 out of 5 at Trip advisor (Trip Advisor, 2017). The reason being, the customer service provided by the competitor is better than the company and the locations of the motel are near to the town at the beachside which provides the convenience to the customers to visits the town as it is only 4 Km. Justification for proposing better value The company can propose the better value by providing the attractive deals especially for the couples and bachelors along with the extended services. Currently, the motel is targeting the people who are travelers for the business meetings or the people having the demand of Beachfront motel but now the company should think to increase the target market by targeting to the bachelors and the customers who want to book the motel for events. Research methods The research method is border term and the core of the research method is Data collection and Data analysis. Beachfront Voyager Motor Inn needs the data collection and analysis to get the details related to the customer value, target market and the competitions value propositions. There are two types of data primary and secondary data (MacKenzie, Podsakoff Podsakoff, 2011). The primary data is the type of the data which was not published before and this data is collected for the specific purpose. On the other hand, the secondary data define as a type of data that was previously published in any of the sources beings its newspapers, books, online portals and journal articles. There are different tools and techniques of information collection that are used by the companies. These methods include observing behavior, Questionnaire method, interviews, and schedules method. Beachfront Voyager Motor Inn makes use of the secondary research method to analyze and gather the details related to the target market and customer value. The interviews and the observations help the motel in understanding the target market and the competitors value proposition (Doz, 2011). The interviews will provide a platform to the customers to express their opinions related to the motel. One of the effective ways to express their opinion about the motel is posting of feedbacks and comments on the online portal that provides the option of booking the motels such as TripAdvisor, MakeMyTrip, Priceline.com and many others. Questionnaires and surveys are one of the popular ways that help the motel in getting the feedback from the customers regarding the services that are liked or disliked. This helps the motel in improving the services which are not liked by the customers and will also try to bring the service which is suggested by the primarily targeted customers (Bryman Bell, 2015). Current value analysis Value analysis is an approach that reflects the value of the products and services that is provided by the company to its customers or potential customers. Customer perceived value The customer perceived value refers to as the value of the product and services for the customers provided by the motel. The motel is trying to provide the best services that lead to the satisfaction of the customers. The company provides the Free Wi-Fi facilities in all the rooms and 16 Foxtel channels. Guest of the Beachfront Voyager Motor Inn can enjoy the facility of the bar, a steak, and a seafood restaurant. Each of the suites of the motel includes the facility of a minibar, ironing facilities, electronic blankets and boast sea and beach views (Beachfront Voyager Motor Inn, 2017). Different customers have diverse perceived value for the location where they are staying. One of the guests Stephen, B has shared his experience with the motel on trip advisor. He stayed in the motel for 2 nights in the separate balcony views and enjoyed the sea view. He shared that the condition and infrastructure of the room were good along with the other facilities like a comfortable couch, table, street parking and the laundry for clothes. Service provided by the motel was impressive and the room was clean, conformable and spacious. A maximum number of guests found that the motel is good. Though, some guest shared that they faced the problems with the noise at the reception and in the hotel (Trip Advisor, 2017). Competitors value analysis The competitors of the motel consist of Beachway Motel Restaurant, Waterfront Lodge Motel, and Mantra Lorne. Out of these competitors, Beachway Motel Restaurant is giving strong competition by providing better facilities to the guests. The Motel provides the spacious and king size bed to the customers with the facility of TV, AC, a mini bar along with attractive and new dcor and carpets. The surroundings offered by motel make them feel like home which enhances the experience of the customers. Moreover, the motel is near to the town on the walking distance and the view of beach impresses the guests (Beachfront Voyager Motor Inn, 2017). The location of the company is one of the reason due to which maximum guest liked the facilities provided by this motel instead of Beachfront Voyager Motor Inn. Current value position of company The current value position of the company is appropriate considering the other competitors expect the Beachway Motel Restaurant as Mantra Lorne is motel at the beachfront is having the rating of 3.5 out of 5 which is almost equal. The current value position of the motel can be evaluated with the use of the value analysis framework which includes the emotional value, symbolic value, functional value, economic value and end value. Emotional value: - The staff of the motel is soft-spoken and helpful which improve the experience of the guests. The values and cultures of the company win the heart of the customers due to this emotional value the guest likes to visits the motel again because they know the values of the company and their staff (Expedia.co.in., 2017). Symbolic value: - The symbolic value reflects the status symbol of the customers if they stay in the motel. The motel comes under the standard hotel that doesnt create any impact on the status symbol of the customers. The company should enhance their symbolic value in the market by bringing new infrastructure and dcor of the motel. Economic value: - The economic value reflects the price that is kept by the motel, the price of the motel is far better than its competitors. In the Beachfront Voyager Motor Inn restaurants, the guest can enjoy the special menu of the seafood for only $18 which is the affordable amount. Affordability of the products and services will make the guest visit the motel again (Beachfront Voyager Motor Inn, 2017). Functional value: - The functional value is related to the process of the motel and the services provided by the motel to its customers. The process of the motel is smooth that ensures that the guests are not facing any difficulties due to a process of a motel. End value: - The end value reflects the satisfaction of the customers which come with the fulfillment of the needs and expectations of the company. Thus, there are many customers who are satisfied with the services provided by the company. These values reflect the current value position of the company and also help in evaluating the performance of the company. If any of the parameters of value is not able to deliver the desired value according to the expectations of the customers then the performance of the company needs improvement. Marketing promotional plan The marketing promotional plan is a strategy that is formed with the motive to promote the products and services offered by the company to its customers. Promotion is the functions of informing, persuading and influencing a purchase decision (Khan, 2014). Objective The objective of the marketing promotion plan is to make use of the 4 promotional mix elements in an effective way to enhance the number of guest and revenue along with the market share of the motel. These 4 promotional mix elements include advertisement, sales promotion, direct marketing and personal selling. The use of the promotional strategy is increasing day by day and most of the motels are making use of the digital communication. The image shows that the hotels and motel involved in the hospitality sector spend approximately 43% in mobile engagement. The mobile engagement of the users is increasing day to day and this is the reason the sector has decided to make use of the digital communication. Advertisement The advertisement is one of the most effective means of communication that is done to generate the awareness about the products and influence the decisions of the customers to purchase the product (Csikosova, Antoov ?ulkov, 2014). For Beachfront Voyager Motor Inn advertisement is essential to make the customer aware of the services that they promise to customers. The motel can make use of the advertisement platform to reach the large audience. The motel should provide the advertisement through print media which include magazine, newspaper, and journals along with the online advertisement. Sales promotion Sales promotion is one of the effective ways through which the company can promote the products in the market. In this type of promotion, the company provides the discount, gifts, coupons, email marketing, samples, rebates, refunds and many other such benefits that help the company in attracting the customers (Obeid, 2014). Beachfront Voyager Motor Inn can make use of the e-mails, discount coupons, and gift coupons through online medium. The deals are provided by the company through an online medium because the motel is aware that the use of the online for checking discount deals is increasing (Huang Sarigll, 2014). Personal selling The personal selling is one of the ways in which the employees of the company directly communicate with the customer and make them aware of the products and services they offer. Through this promotion mix, the Beachfront Voyager Motor Inn can provide the details related to the services which might help the company in grabbing the attention of the customers. Direct marketing Direct marketing used by the company that emphasis on promoting the specific product or service. There are different types of direct marketing such as SMS marketing, E-mail marketing, social media marketing or digital marketing (Lund Marinova, 2014). Beachfront Voyager Motor Inn is making the use of the social media technology for promoting the products as the company has provided the details related to the products and services through Facebook, one of the effective social media channel (Mangold Faulds, 2009). It is suggested to the company to start making the use of the other channels (Twitter, Instagram, and LinkedIn) for promoting products. Promotional Budget Digital Communication Budget Method Amount 1. Direct Marketing Online media Facebook $800.00 Twitter $1,000.00 LinkedIn $1,200.00 E-mail Marketing $400.00 Total Amount of Online Media through Direct marketing $3,400.00 2. Advertisement Print Media Newspaper $800.00 Journals $1,200.00 Online advertisement $600.00 Total amount of Advertisement $2,600.00 3. Personal selling Conducting Seminar and training $1,000.00 Funding $600.00 Total amount of Personal selling $1,600.00 4. Sales promotion Discount Coupons $500.00 Gift coupons $1,000.00 Total amount of sales promotion $1,500.00 Total amount $9,100.00 Conclusion The report is based on the Beachfront Voyager Motor Inn, a local motel situated in Australia. There is brief description related to the company and its target market along with the value proposition of the company. The consultant of the company performed the analysis to bring the improvement in the value analysis of the company. There are different methods that are used by the consultant to research the details related to the target market, company value and competitors value analysis. Moreover, the report includes the current value analysis along with the marketing promotional plan which includes the promotional strategy of the company along with the companys budget. References Beachfront Voyager Motor Inn. (2017). About Us. Viewed on 20th January 2018. https://www.beachfrontvoyager.com.au/about-us.html Beachfront Voyager Motor Inn. (2017). Rooms. Viewed on 20th January 2018. https://www.beachfrontvoyager.com.au/rooms.html Bernard, H. R. (2017).Research methods in anthropology: Qualitative and quantitative approaches. Rowman Littlefield. Bowie, D., Buttle, F., Brookes, M., Mariussen, A. (2016).Hospitality marketing. Taylor Francis. Bryman, A., Bell, E. (2015).Business research methods. Oxford University Press, USA. Caroll, J. (2016). Future Trends in the Hospitality Industry: Millennials and Social Media Rule. Viewed on 20th January 2018. https://www.callboxinc.com/b2b-marketing-and-strategy/future-trends-in-hospitality-industry-millennials-and-social-media-rule/ Csikosova, A., Antoov, M., ?ulkov, K. (2014). Strategy in direct and interactive marketing and integrated marketing communications.Procedia-Social and Behavioral Sciences,116, 1615-1619. Doz, Y. (2011). Qualitative research for international business.Journal of International Business Studies,42(5), 582-590. Expedia.co.in. (2017). Beachfront Voyager Motor Inn. Viewed on 20th January 2018. https://www.expedia.co.in/Northwest-Tasmania-Hotels-Beachfront-Voyager-Motor-Inn.h519143.Hotel-Information?langid=2057regionId=11702semcid=IN.UB.GOOGLE.SEARCH.HOTELkword=ind_eng_int_pt_dsa_feed!e.ZzZz.4910001680612.0.196018754559..ind_eng_int_pt_dsa_feedsemdtl=a1630610720.b132157993320.d1196018754559.e1c.f11t1.g1aud-168216765194:dsa-286574005915.h1b.i19408736449.j19061783.k1.l1g.m1.n1gclid=EAIaIQobChMIv9azwojm2AIVyROPCh1eHwKAEAAYASAAEgL0avD_BwE Fusch, P. I., Ness, L. R. (2015). Are we there yet? Data saturation in qualitative research.The Qualitative Report,20(9), 1408. Hollensen, S. (2015).Marketing management: A relationship approach. Pearson Education. Huang, R., Sarigll, E. (2014). How brand awareness relates to market outcome, brand equity, and the marketing mix. InFashion Branding and Consumer Behaviors(pp. 113-132). Springer New York. Khan, M. T. (2014). The concept of'marketing mix'and its elements (a conceptual review paper).International journal of information, business and management,6(2), 95. Lapidoth, A. (2017).A foundation in digital communication. Cambridge University Press. Lund, D. J., Marinova, D. (2014). Managing revenue across retail channels: The interplay of service performance and direct marketing. American Marketing Association. MacKenzie, S. B., Podsakoff, P. M., Podsakoff, N. P. (2011). Construct measurement and validation procedures in MIS and behavioral research: Integrating new and existing techniques.MIS quarterly,35(2), 293-334. Mangold, W. G., Faulds, D. J. (2009). Social media: The new hybrid element of the promotion mix.Business horizons,52(4), 357-365. Obeid, M. Y. (2014). The effect of sales promotion tools on behavioral responses.International Journal of Business and Management Invention,3(4), 28-31. Prince Line. (2017). Beachfront Voyager Motor Inn. Viewed on 20th January 2018. https://www.priceline.com/beachfront-voyager-motor-inn-burnie-tasmania-128256-hd.hotel-reviews-hotel-guides#details Tasmanias North West. (2017). Beachfront Voyager Motor Inn. Viewed on 20th January 2018. https://tasmaniasnorthwest.com.au/accommodation/beachfront-voyager-motor-inn/ Trip Advisor. (2017). Beachfront Voyager Motor Inn. Viewed on 20th January 2018. https://www.tripadvisor.in/Hotel_Review-g504286-d1793872-Reviews-Beachfront_Voyager_Motor_Inn-Burnie_Tasmania.html Trip Advisor. (2017). Beachway. Viewed on 20th January 2018. https://www.tripadvisor.in/Hotel_Review-g504333-d1597874-Reviews-Beachway-Ulverstone_Tasmania.html

Tactics in Negotiations

Introduction Just like many other business processes, there is an increasing need to use the principles of management during business negotiation. These principles include planning, organizing, directing and controlling. They aid in attaining completeness, as far as business negotiation processes are concerned. This paper explores the need to embrace each of these principles during business negotiation.Advertising We will write a custom essay sample on Tactics in Negotiations specifically for you for only $16.05 $11/page Learn More Essence of planning, organizing, directing and controlling According to Lewicki and Hiam (2006), businesses negotiation comprises of different processes. This is why there is need to have adequate preparation for negotiation. Strategic planning is vital since it ensures that all the issues to be negotiated about are identified and clearly understood by the negotiating team. Planning also helps in addressing the critical issues that need to be captured during the entire process. This ensures that there is flow in negotiation. Organizing is another critical managerial principle in business negotiation. Organizing comes in during the pre-phases of negotiation. The essentiality of organizing during business negotiation revolves around the logistical issue that appertain the negotiation. Issues of venue, time, listing of issues to be negotiated about, and the approaches to be deployed in the process of negotiation are brought out (Lewicki Hiam 2006). Directing ensures that a certain level of command is attained by the negotiators in line with the main goals of the firm; which mostly revolve around business sustainability and profit making. Controlling ensures that the desired procedures are strictly adhered to during negotiation. Controlling also ensures that a desired level of flexibility is attained during the give and take part of the negotiation to ensure that the goals of a company are attained. Skills and competencies for effective business negotiation Business firms operate under a competitive environment. To this effect, any business negotiator has to be familiar with the prevailing aspects’ competitive dynamics in the market and the essential business strategies that can be used by firms to help ease the competitive pressure. Therefore, the first vital skill in business negotiation is to understand the microeconomic and macroeconomic dynamics in the business environment and how they affect the operations of a firm (Garrett, 2005). The main reason why a firm engages in business negotiations is to secure outcomes that can aid in increasing the business payoffs for the company. Therefore, business negotiators have to understand the business goals and objectives of the company in order to further them during the negotiations. This also entails understanding the business goals and objectives of the business partners in order to make reasonable demands and adjustments during the negotiation (Lewicki Hiam, 2006). Essence of understanding and applying different strategies of negotiation Several communicative attributes and strategies are deployed during business negotiation. Each of the strategies are applied with the aim of either ensuring that the negotiation flows or ensuring possible maximum payoffs are attained by the negotiating team. The planning stage in business negotiation entails the rehearsal stage.Advertising Looking for essay on business economics? Let's see if we can help you! Get your first paper with 15% OFF Learn More Rehearsal is meant to ensure that all the strategies that are to be used during business negotiation are mastered by the negotiating team. The technical areas of each of the strategies are developed during the rehearsals. The strategies that are deployed by a given team in the process of negotiation ought to be patterned by counter strategies from the other team. This implies that a mastery of massive busine ss negotiation strategies can help a firm to adjust and attain favorable outcomes (Cellich Jain, 2012). References Cellich, C., Jain, S. C. (2012). Practical solutions to global business negotiations. New York, NY: Business Expert Press. Garrett, G. A. (2005). Contract negotiations: Skills, tools, and best practices. Chicago, IL: CCH. Lewicki, R. J., Hiam, A. (2006). Mastering business negotiation: a working guide to making deals and resolving conflict. San Francisco, CA: Jossey-Bass. This essay on Tactics in Negotiations was written and submitted by user Jadiel K. to help you with your own studies. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly. You can donate your paper here.

Free Essays on Which Road

Which road you choose makes you who you are. Everyone is a traveler, and his or her journey is life. There is never a straight path that leaves one with a sole direction in which to head. Regardless of the original message that Robert Frost had intended to convey, his poem, â€Å"The Road Not Taken†, has left its readers with many different interpretations. It is one’s past, present, and the attitude with which he looks upon his future that determines light that he will see the poem in. In any case, this poem clearly demonstrates Frost’s belief that it is the road a person chooses that makes him the man he is. Frost says, â€Å"and sorry I could not travel both†¦Ã¢â‚¬  It is always difficult to make a decision because it is impossible not to wonder about the opportunity cost, what will be missed out on. There is a strong sense of regret before the choice is even made. The knowledge that in one lifetime it is impossible to travel down every path is upsetting to some people. In an attempt to make a decision, the traveler â€Å"looks down one as far as I could†. The road that will be chosen leads to the unknown, as does any choice in life. As much as he may strain his eyes to see what is down the road, eventually it surpasses his vision and he can never really see where the road is going to lead. The path that he chooses will set him off on his journey and decide where he is going. â€Å"Then took the other, just as fair, and having perhaps the better claim†. What made it have the better claim is that â€Å"it was grassy and wanted wear†. It was something obviously not for everyone because it seemed that the majority of people took the other path. Therefore, he calls it â€Å"the road less traveled by†. The fact that the traveler took this path over the more popular is a clear indicator as to his character. He is very secure and doesn’t necessarily need to follow the crowd but would rather do his own thi... Free Essays on Which Road Free Essays on Which Road Which road you choose makes you who you are. Everyone is a traveler, and his or her journey is life. There is never a straight path that leaves one with a sole direction in which to head. Regardless of the original message that Robert Frost had intended to convey, his poem, â€Å"The Road Not Taken†, has left its readers with many different interpretations. It is one’s past, present, and the attitude with which he looks upon his future that determines light that he will see the poem in. In any case, this poem clearly demonstrates Frost’s belief that it is the road a person chooses that makes him the man he is. Frost says, â€Å"and sorry I could not travel both†¦Ã¢â‚¬  It is always difficult to make a decision because it is impossible not to wonder about the opportunity cost, what will be missed out on. There is a strong sense of regret before the choice is even made. The knowledge that in one lifetime it is impossible to travel down every path is upsetting to some people. In an attempt to make a decision, the traveler â€Å"looks down one as far as I could†. The road that will be chosen leads to the unknown, as does any choice in life. As much as he may strain his eyes to see what is down the road, eventually it surpasses his vision and he can never really see where the road is going to lead. The path that he chooses will set him off on his journey and decide where he is going. â€Å"Then took the other, just as fair, and having perhaps the better claim†. What made it have the better claim is that â€Å"it was grassy and wanted wear†. It was something obviously not for everyone because it seemed that the majority of people took the other path. Therefore, he calls it â€Å"the road less traveled by†. The fact that the traveler took this path over the more popular is a clear indicator as to his character. He is very secure and doesn’t necessarily need to follow the crowd but would rather do his own thi...

Maths Construction Essay Example | Topics and Well Written Essays - 500 words

Maths Construction - Essay Example At 50⠁ °C the resistance is found to be 25.6 ohms and at 95⠁ °C the resistance is 36.2 ohms respectively. Find R0 and ÃŽ ± both algebraically and using graphical methods. Using graphical methods determines the resistance at 72⠁ °C. d) As an employee of company JR construction you have received a letter from a regarding the project your company is working on. It has a penalty clause that states the contractor will forfeit a certain sum of money each day for late completion. (I.e. The contractor gets paid the value of the original contract less any sum forfeit). If she is 5 days late, she receives  £4250 and if she is 12 days late she receives  £2120. Calculate the daily forfeit and determine the original contract value. Use both algebraic and matrix methods to solve this. e) Excel Electrical specializes in the batch production of electrical switchgear used in building services installations. The company has been asked to tender for equipment to be fitted in several hundred new stores planned by Setco Supermarkets. Data is available from ten previous production runs of components. c) Outline and apply an alternative means of assessing whether or not a linear relationship exists between the variables and determining the equation linking the two variables. Present and explain your conclusions. . (Singh & Baker, 2007, p.

Toyota Motor Corporation Essay Example | Topics and Well Written Essays - 2250 words

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Smart Music Player Integrating Facial Emotion Recognition

Smart Music Player Integrating Facial Emotion Recognition Smart Music Player Integrating Facial Emotion Recognition and Music Mood Classification 1Shlok Gilda, 2Husain Zafar, 3Chintan Soni, 4Kshitija Waghurdekar Department of Computer Engineering, Pune Institute of Computer Technology, Pune, India Abstract Songs, as a medium, have always been a popular choice to depict human emotions. Reliable emotion based classification systems can go a long way in facilitating this. However, research in the field of emotion based music classification has not yielded optimal results. In this paper, we present an affective cross-platform music player, EMP, which recommends music based on the real-time mood of the user. EMP provides smart mood based music recommendation by incorporating the capabilities of emotion context reasoning within our adaptive music recommendation system. Our music player contains three modules: Emotion Module, Music Classification Module and Recommendation Module. The Emotion Module takes an image of the user as an input and makes use of deep learning algorithms to identify the mood of the user with an accuracy of 90.23%. The Music Classification Module makes use of audio features to achieve a remarkable result of 97.69% while classifying songs into 4 different mood c lasses. The Recommendation Module suggests songs to the user by mapping the emotion of the user to the mood of the song, taking into consideration the preferences of the user. Keywords-Recommender systems, Emotion recognition, Music information retrieval, Artificial neural networks, Multi-layer neural network. I. Introduction Current research in the field of music psychology has shown that music induces a clear emotional response in its listeners[1]. Musical preferences have been demonstrated to be highly correlated with personality traits and moods. The meter, timber, rhythm and pitch of music are managed in areas of the brain that deal with emotions and mood[2]. Undoubtedly, a users affective response to a music fragment depends on a large set of external factors, such as gender, age[3], culture[4], preferences, emotion and context[5] (e.g. time of day or location). However, these external variables set aside, humans are able to consistently categorize songs as being happy, sad, enthusiastic or relaxed. Current research in emotion based recommender systems focuses on two main aspects, lyrics[6][12] and audio features[7]. Acknowledging the language barrier, we focus on audio feature extraction and analysis in order to map those features to four basic moods. Automatic music classification using some mood categories yields promising results. Expressions are the most ancient and natural way of conveying emotions, moods and feelings. The facial expression would categorize in 4 different emotions, viz. happy, sad, angry and neutral. The main objective of this paper is to design a cost-effective music player which automatically generates a sentiment aware playlist based on the emotional state of the user. The application designed requires less memory and less computational time. The emotion module determines the emotion of the user. Relevant and critical audio information from a song is extracted by the music classification module. The recommendation module combines the results of the emotion module and the music classification module to recommend songs to the user. This system provides significantly better accuracy and performance than existing systems. II. Related Works Various methodologies have been proposed to classify the behaviour and emotional state of the user. Mase et al. focused on using movements of facial muscles[8] while Tian et al.[9] attempted to recognize Actions Units (AU) developed by Ekman and Friesen in 1978[10] using permanent and transient facial features. With evolving methodologies, the use of Convolutional Neural Networks (CNNs) for emotion recognition has become increasingly popular[11]. Music has been classified using lyrical analysis[6][12]. While this tokenized method is relatively easier to implement, on its own, it is not suitable to classify songs accurately. Another obvious concern with this method is the language barrier which restricts classification to a single language. Another method for music mood classification is using acoustic features like tempo, pitch and rhythm to identify the sentiment conveyed by the song. This method involves extracting a set of features and using those feature vectors to find patterns characteristic to a specific mood. III. Emotion Module In this section, we study the usage of convolutional neural networks (CNNs) to emotion recognition[13][14]. CNNs are known to simulate the human brain when analyzing visuals; however, given the computational requirements and complexity of a CNN, optimizing a network for efficient computation is necessary. Thus, a CNN is implemented to construct a computational model which successfully classifies emotion in 4 moods, namely, happy, sad, angry and neutral, with an accuracy of 90.23%. A.   Dataset Description The dataset we used for training the model is from a Kaggle Facial Expression Recognition Challenge, FER2013[15]. The data consists of 4848 pixel grayscale images of faces. Each of the faces are organized into one of the 7 emotion classes: angry, disgust, fear, happy, sad, surprise, and neutral. For this research, we have made use of 4 emotions: angry, happy, sad and neutral. There is a total of 26,217 images corresponding to these emotions. The breakdown of the images is as follows: happy with 8989 samples, sad with 6077 samples, neutral with 6198 samples, angry with 4953 samples. B. Model Description A multi-layered convolutional neural network is programmed to evaluate the features of the user image[16][17]. The convolutional neural network contains an input layer, some convolutional layers, ReLU layers, pooling layers, and some dense layers (aka. fully-connected layers), and an output layer. These layers are linearly stacked in sequence. 1) Input Layer: The input layer has fixed and predetermined dimensions. So, for pre-processing the image, we used OpenCV for face detection in the image before feeding the image into the layer. Pre-trained filters from Haar Cascades along with Adaboost are used to quickly find and crop the face. The cropped face is then converted into grayscale and resized to 48-by-48 pixels. This step greatly reduces the dimensions from (3, 48, 48) (RGB) to (1, 48, 48) (grayscale) which can be easily fed into the input layer as a numpy array. 2) Convolutional Layers:A set of unique kernels (or feature detectors), with randomly generated weights, are specified as one of the hyperparameters in the Convolution2D layer. Each feature detector is a (3, 3) receptive field, which slides across the original image and computes a feature map. Convolution generates different feature maps for the same input image. Distinct filters are used to perform operations that represent how pixel values are enhanced, for example, blur and edge detection. Filters are applied successively over the entire image, creating a set of feature maps. In our neural network, each convolutional layer generates 128 feature maps. Rectified Linear Unit (ReLU) has been used after every convolution operation. After a set of convolutional layers, a popular pooling method, MaxPooling, was used to reduce the dimensionality of each feature map, all the while retaining the critical information. We used (2, 2) windows which consider only the maximum pixel values within the window from the feature map. The pooled pixels form an image with dimensions reduced by 4. Rectified Linear Unit (ReLU) has been used after every convolution operation. 3) Dense Layers:The output from the convolutional and pooling layers represent high-level features of the input image. The dense layer uses these features for classifying the input image into various classes. The features are transformed through the layers which are connected with trainable weights. The network is trained by forward propagation of training data and then backward propagation of its errors. Our model uses 2 sequential fully connected layers. The network generalizes well to new images and is able to gradually make adjustments until the errors are minimized. A dropout of 20% was applied in order to prevent overfitting of the training data. This helped us control the models sensitivity to noise during training while maintaining the necessary complexity of the architecture. 4) Output Layer:We used softmax as the activation function at the output layer of the dense layer. Thus, the output is represented as a probability distribution for each emotion class. Models with various combinations of hyper-parameters were trained and evaluated utilizing a 4 GiB DDR3 NVIDIA 840M graphics card using the NVIDIA CUDA ® Deep Neural Network library (cuDNN). This greatly reduced training time and increased efficiency in tuning the model. Ultimately, our network architecture consisted of 9 convolutional layers with one max-pooling after every three convolution layers followed by 2 dense layers, as seen in Figure 1. C. Results The final network was trained on 20973 images and tested on 5244 images. At the end, the model achieved an accuracy of 90.23%. Table 1 displays the confusion matrix for the module. Evidently, the system performs very well in classifying images belonging to the angry category. We also note interesting results under happy and sad category owing to the remarkable differences in Action Units as mentioned by Ekman[11]. The F-measure of this system comes out to be 90.12%. IV. Music Classification Module In this section, we describe the procedure that was used to identify the mapping of each song with its mood. We extracted the acoustic features of the songs using LibROSA[18], aubiopitch[19] and other state-of-the art audio extraction algorithms. Based on these features, we trained an artificial neural network which successfully classifies the songs in 4 classes with an accuracy of 92.05%. The classification process is described in Figure 2. A.Dataset Description The dataset comprises of 390 songs spread across four moods. The distribution of the songs is as follows: class A with 100 songs, class B with 93 songs, class C with 100 songs and class D with 97 songs. The songs were manually labelled and the class labels were verified by 10 paid subjects. Class A comprises of exciting and energetic songs, class B has happy and joyful songs, class C consists of sad and melancholy songs, and class D has calm and relaxed songs. 1) Preprocessing: All the songs were down sampled to a uniform bit-rate of 128 kbps, a mono audio channel and resampled at a sampling frequency of 44100 Hz. We further split each song to obtain clips that contained the most meaningful parts of the song. The feature vectors were then standardized so that it had zero mean and a unit variance. 2) Feature Description: We identified several mood sensitive audio features by reading current works[20] and the results from the 2007 MIREX Audio Mood Classification task[21][22]. The candidate features for the extraction process belonged to different classes: spectral (RMSE, centroid, rolloff, MFCC, kurtosis, etc.), rhythmic (tempo, beat spectrum, etc.), tonal mode and pitch. All these descriptions are standard. All the features were extracted using Python 2.7 and relevant packages[18][19]. After identifying all the features, we used Recursive Feature Elimination (or RFE) to select those features that best contribute to the accuracy of the model. RFE works by recursively removing attributes and building a model on those attributes that remain. It uses the model accuracy to identify which attributes (and combination of attributes) contribute the most to predicting the target attribute. The selected features were pitch, spectral rolloff, mel-frequency cepstral coefficients, tempo, root mean square energy, spectral centroid, beat spectrum, zero-cross rate, short-time Fourier transform and kurtosis of the songs. B. Model Description A multi-layered neural network was trained to evaluate the mood associated with the song. The network contains an input layer, multiple hidden layers and a dense output layer. The input layer has fixed and predetermined dimensions. It takes the 10 feature vectors as input and uses ReLU operation to provide non-linearity to the dataset. This ensured that the model performs well in real-world scenarios as well. The hidden layer is a traditional multi-layer perceptron, which allowed us to make combination of features which led to a better classification accuracy. The output layer used a softmax activation function which produces the output as a probability for each mood class. C. Results We achieved an overall classification accuracy of 97.69% and F1 score of 97.692% after 10-fold cross-validation using our neural network. Table 2 displays the confusion matrix. Undoubtedly, the level of performance of the music classification module is exceptionally high. V. Recommendation Module This module is responsible for generating a playlist of relevant songs for the user. It allows the user to modify the playlist based on her/his preferences and modify the class labels of the songs as well. The working of the recommendation module is explained in Figure 3. A. Mapping and Playlist Generation Classified songs are mapped to the users mood. This mapping is as shown in figure 1. The system was developed after referring to the Russell 2-D Valence-Arousal Model and Geneva Emotion Wheel.After the mapping procedure is complete, a playlist of relevant songs is generated. Similar songs are grouped together while generating the playlist. Similarity between songs was calculated by comparing songs over 50ms intervals, centered on each 10ms time window. After empirical observations, we found that the duration of these intervals is on the order of magnitude of a typical song note. Cosine distance function was used to determine the similarity between audio files. Feature values corresponding to an audio file were compared to the values (for the same features) corresponding to audio files belonging to the same class label. The recommendation engine has a twofold mechanism; it recommends songs based on: 1. Users perceived mood. 2. Users preference. Initially, a playlist of all songs belonging to the particular class is generated. The user can mark a song as favorite depending on her/his choice. A favorite song will be assigned a higher priority value in the playlist. Also, the interpretation of the mood of a song can vary from person to person. Understanding this, the user is allowed to change the class label of the songs according to their taste of music. B. Adaptive Music Player We were able to implement an adaptive music player by the use of a very popular online machine learning algorithm, Stochastic Gradient Descent (SGD)[23]. If the user wants to change the class of a particular song, SGD is implemented considering the new label for that specific user only. Multiple single-pass algorithms were analyzed for their performance with our system but SGD performed most efficiently considering the real-time nature of the music player. Parameter updates in SGD occur after processing of every training example from the dataset. This approach yields two advantages over the batch gradient descent algorithm. Firstly, time required for calculating the cost and gradient for large datasets is reduced. Secondly, integration of new data or amendment of existing data is easier. The frequent, highly variant updates demand the learning rate ÃŽÂ ± to be smaller as compared to that of batch gradient descent[23]. VI. Conclusion The results obtained above are very promising. The high accuracy of the application and quick response time makes it suitable for most practical purposes. The music classification module in particular, performs significantly well. Remarkably, it achieves high accuracy in the angry category; it also performs specifically well for the happy and calm categories. Thus, EMP reduces user efforts for generating playlists. It efficiently maps the user emotion to the song class with an excellent overall accuracy, thus achieving optimistic results for 4 moods. References [1] Swathi Swaminathan, E. Glenn Schellenberg. Current Emotion Research in Music Psychology, Emotion Review Vol. 7, No. 2, pp. 189 ­-197, April 2015 [2] How music changes your mood, Examined Existence. [Online]. Available: http://examinedexistence.com/how-music-changes-your-mood/. Accessed: Jan. 13, 2017 [3] Kyogu Lee and Minsu Cho. Mood Classification from Musical Audio Using User Group-dependent Models. [4] Daniel Wolff, Tillman Weyde and Andrew MacFarlane. Culture-aware Music Recommendation [5] Mirim Lee, Jun-Dong Cho. Logmusic: Context-Based Social Music Recommendation Service on Mobile Device, Ubicomp 14 Adjunct, September 13-17, 2014, Seattle, WA, USA. [6] D. Gossi and M. H. Gunes, Lyric-based music recommendation, in Studies in Computational Intelligence. Springer Nature, 2016, pp. 301-310. [7] Bo Shao, Dingding Wang, Tao Li, and Mitsunori Ogihara. Music Recommendation Based on Acoustic Features and User Access Patterns, IEEE TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 17, NO. 8, NOVEMBER 2009 [8] Mase K. Recognition of facial expression from optical flow. IEICE Transc., E. 74(10):3474-3483, 0ctober 1991. [9] Tian, Ying-li, Kanade, T. and Cohn, J. Recognizing Lower. Face Action Units for Facial Expression Analysis. Proceedings of the 4th IEEE International Conference on Automatic Face and Gesture Recognition (FG00), March, 2000, pp. 484 490. [10] Ekman, P., Friesen, W. V. Facial Action Coding System: A Technique for Measurement of Facial Movement. Consulting Psychologists Press Palo Alto, California, 1978. [11] Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns [12] E. E. P. Myint and M. Pwint, An approach for mulit-label music mood classification, 2010 2nd International Conference on Signal Processing Systems, Dalian, 2010, pp. V1-290-V1-294. [13] Peter Burkert, Felix Trier, Muhammad Zeshan Afzal, Andreas Dengel and Marcus Liwicki. DeXpression: Deep Convolutional Neural Network for Expression Recognition [14] Ujjwalkarn, An intuitive explanation of Convolutional neural networks, the data science blog, 2016. [Online]. Available: https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/. Accessed: Jan. 13, 2017. [15] Ian J. Goodfellow et al., Challenges in Representation Learning: A report on three machine learning contests [16] S. Lawrence, C. L. Giles, Ah Chung Tsoi and A. D. Back, Face recognition: a convolutional neural-network approach, in IEEE Transactions on Neural Networks, vol. 8, no. 1, pp. 98-113, Jan 1997. [17] A. KoÅ‚akowska, A. Landowska, M. Szwoch, W. Szwoch, and M. R. WrÃÅ' obel, Human-Computer Systems Interaction: Back-grounds and Applications 3, ch. Emotion Recognition and Its Applications, pp. 51-62. Cham: Springer International Publishing, 2014. [18] Brian McFee, ., Matt McVicar, ., Colin Raffel, ., Dawen Liang, ., Oriol Nieto, ., Eric Battenberg, ., à ¢Ã¢â€š ¬Ã‚ ¦ Adrian Holovaty, . (2015). librosa: 0.4.1 [Data set]. Zenodo. http://doi.org/10.5281/zenodo.32193 [19] The aubio team, Aubio, a library for audio labelling, 2003. [Online]. Available: http://aubio.org/. Accessed: Jan. 13, 2017. [20] E. E. P. Myint and M. Pwint, An approach for mulit-label music mood classification, 2010 2nd International Conference on Signal Processing Systems, Dalian, 2010, pp. V1-290-V1-294. [21] J. S. Downie. The music information retrieval evaluation exchange  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   (mirex). D-Lib Magazine, 12(12), 2006. [22]  Ãƒâ€šÃ‚   Cyril Laurier, Perfecto Herrera, M Mandel and D Ellis,Audio music mood classification using support vector machine [23] Unsupervised feature learning and deep learning Tutorial, [Online]. Available: http://ufldl.stanford.edu/tutorial/supervised/OptimizationStochasticGradientDescent/. Accessed: Jan. 13, 2017

Sex Education Taught to 8 Year Olds

Eight-year-old children are being targeted for more detailed sex education in schools. In Christchurch today, Family Planning is launching a new resource for teachers of late-primary and intermediate-age children. The launch has upset the conservative lobby group Family First, which is urging Family Planning to â€Å"butt out† and leave sex education to parents. The resource, called The Sexuality Road, is aimed at younger children because research shows that they are now entering puberty earlier. Young people have a right to understand what is happening to their bodies and their emotions,† Family Planning director of health promotion Frances Bird said. â€Å"Sexuality education that works starts early, before young people reach puberty, and before they have developed established patterns of behavior. † The Sexuality Road provides teachers with a programme of 10 lessons and evaluations per year. Each year comes with lesson plans, activity worksheets, and resources. Year 5 and 6 (nine and 10-year-old) pupils look at pubertal change, friendships, gender, families, menstruation, fertility, conception and personal support. Year 7 and 8 pupils focus more on changing feelings and emotions and their effects on relationships, sexual attraction, decision-making around sexual attraction, conception and birth, contraception and support agencies. Bird said international evidence showed children were entering puberty earlier than had been seen in decades. The average age of puberty for girls in New Zealand had fallen to between nine and 14 and for boys, it was between 11 and 16, Bird said. â€Å"Some people are concerned that providing information about sex and sexuality arouses curiosity and can lead to sexual experimentation. There is no evidence that this happens,† she said. New Zealand teenagers rate second-highest in the developed world for teen pregnancies. The Press last month revealed research showing more than a third of 16-year-olds have already had sex and half say they have been in love. An Education Review Office report, commissioned by the ministries of Women's Affairs, Health and Education, found at least half of all sex education in schools was presented by teachers with no qualifications in the subject. Liggins Institute director, and newly appointed chief science adviser, Professor Peter Gluckman has earlier called for action to address the â€Å"emerging national crisis,† in sex education for younger children. â€Å"Sex and health education has to become mainstream and away from the idea that it's only for the physed teacher who is least equipped to deal with it,† Gluckman said. Family First national director Bob McCoskrie said children should be taught sex education by their parents when they were ready. â€Å"The simple message to Family Planning is `butt out and leave it to parents',† McCoskrie said. Parents know their kids the best. They know their emotional and moral development best and have their own values. Family Planning should not be interacting with kids of that age. † McCoskrie said schools had become â€Å"one-stop shops† for dealing with social problems in the community. Some parents felt overawed by â€Å"the sex talk† with their children, so resources should be put in to helping them better understand what was required, McCoskrie said. â€Å"It needs to be values-based and we think parents are the ones who determine the values. Bird said children should be exposed to a range of values, attitudes and opinions. According to a survey run on the Netmums parenting website, the majority of parents believe children should start learning about sex and relationships when they are eight years old. I can hear them already. The shocked and outraged tones of the other â€Å"moral† majority reacting to yet another progressive plot to corrupt children. â€Å"We'll have no sex education here! † Or if we must, let them wait until they're actually doing it. That is sad, because such views are themselves transformative, turning sex from a natural and evolving topic to a dangerous threshold, making childhood sexualisation more, not less, likely. Talking about sex starts much earlier transforms the likelihoods that children will be better informed. Children use sexual terms long before they reach the age of eight (year 3). Listening recently to year 1 conversations, I overheard boys talking about â€Å"having sex† (they mean â€Å"cuddling†). They insult each other using terms such as â€Å"gay†. Discussion of sex runs through the playground discourse like Blackpool through a stick of rock: it's just very badly formed. Talking about sex needs to start earlier so that children will not be confused at a leter time when it is learned thru their peer group. A straw poll of local school kids suggests little useful sex education is received before the age of 13. That's two years after the average age at which girls begin their periods – five years after some. If you're not told about such stuff at home, how terrifying to be eight and suddenly bleeding. A range of studies report puberty starting earlier in western societies – and while the reality of sexual experimentation may not be as graphic or extreme as the tabloids would have us believe, that, too, can begin long before 13. Sexual orientation and identity, too, can be obvious at a very early age (from six onward): once more, how scary to grow in an atmosphere that makes â€Å"queers† always the butt of jokes with no balancing official information. Sex doesn't have to be sexual in nature. Many of the dirtiest, smuttiest most adult things about sex are just that: adult. There is a depressing read-across from adult values to child: many people assume that a child doing something â€Å"sexy† understands their behavior and intends the result. Children learn through play. Girls dress, use makeup and dance in ways that would be erotic if their mums did them – but absolutely aren't when they do. Children can be educated about sex without focusing on the erotic. It's never too young to learn respect for the beliefs of sexually actions. The most misleading thing about this debate is that opponents caricature sex education as being about just one thing. In fact, broad and structured sex education will provide grounding in relationships, biology, safety, health, respect for others and consent. These will be introduced at the appropriate point using language appropriate to the age discovering them. In a world in which many adult relationships continue to be conducted through the emotions of childhood – and one in four women (and one in five men) are still suffering domestic violence – early sex ed is as much about learning the most basic of lessons – the right to say no – as anything else.